Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

Interactive visualization for opportunistic exploration of large document collections

Presenter : Chun-Ping Wu　Authors :Simon Lehmann, Ulrich Schwanecke, Ralf Dorner

IS 2010

國立雲林科技大學National Yunlin University of Science and Technology

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Motivation

Finding relevant information in a large and comprehensive collection of cross-referenced documents like Wikipedia usually requires a quite accurate idea where to look for the pieces of data being sought.

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Objective

This paper describes the interactive visualization Wivi which enables users to intuitively navigate Wikipedia by visualizing the structure of visited articles and emphasizing relevant other topics.

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

The current Degree of interest(DOI) of an article v:

A-priori-importance(API) of the unvisited articles can be formally defined as

The temporal distance D of an unvisited article v can then be defined as

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

The architecture of Wivi.

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Conclusion

99

The approach combines both a visualization of visited articles and articles that could be immediately reached from all visited articles.

It also calculates a degree of interest of the unvisited articles based on the structure and history of the article graph.

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Comments

1010

Advantage The system is very interesting. The approach can help users more easily to read.

Drawback When a large amount of data, the system performance is poor.

Application Browsing, Searching